Google functions example

deploy.py

import pandas as pd
import numpy as np
import logging
from google.cloud import storage
from lightgbm import LGBMRegressor
from sklearn.externals import joblib
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import OrdinalEncoder

num_feat = ['MSSubClass', 'LotFrontage', 'LotArea',
            'OverallQual', 'OverallCond', 'YearBuilt',
            'YearRemodAdd', 'MasVnrArea', 'BsmtFinSF1',
            'BsmtFinSF2', 'BsmtUnfSF', 'TotalBsmtSF',
            '1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea',
            'BsmtFullBath', 'BsmtHalfBath', 'FullBath',
            'HalfBath', 'BedroomAbvGr', 'KitchenAbvGr',
            'TotRmsAbvGrd', 'Fireplaces', 'GarageYrBlt',
            'GarageCars', 'GarageArea', 'WoodDeckSF',
            'OpenPorchSF', 'EnclosedPorch', '3SsnPorch',
            'ScreenPorch', 'PoolArea', 'MiscVal', 'MoSold', 'YrSold'
]

cat_feat = ['MSZoning', 'Street', 'Alley', 'LotShape',
            'LandContour', 'Utilities', 'LotConfig',
            'LandSlope', 'Neighborhood', 'Condition1',
            'Condition2', 'BldgType', 'HouseStyle', 'RoofStyle',
            'RoofMatl', 'Exterior1st', 'Exterior2nd', 'MasVnrType',
            'ExterQual', 'ExterCond', 'Foundation', 'BsmtQual',
            'BsmtCond', 'BsmtExposure', 'BsmtFinType1', 'BsmtFinType2',
            'Heating', 'HeatingQC', 'CentralAir', 'Electrical',
            'KitchenQual', 'Functional', 'FireplaceQu', 'GarageType',
            'GarageFinish', 'GarageQual', 'GarageCond', 'PavedDrive',
            'PoolQC', 'Fence', 'MiscFeature', 'SaleType', 'SaleCondition'
]

def download_model():
    logging.info('Downloading resources GCloud -> /tmp...')
    client = storage.Client()
    bucket = client.get_bucket('up_teaching_2019')
    # download encoder
    blob_enc = storage.Blob('model/house_pricing/enc.joblib', bucket)
    blob_enc.download_to_filename('/tmp/enc.joblib')
    # download imputer
    blob_imp = storage.Blob('model/house_pricing/imp.joblib', bucket)
    blob_imp.download_to_filename('/tmp/imp.joblib')
    # download model
    blob_model = storage.Blob('model/house_pricing/model.joblib', bucket)
    blob_model.download_to_filename('/tmp/model.joblib')

def predict(data):
    logging.info('Making predictions...')
    logging.info(data)
    # load models
    imp = joblib.load('/tmp/imp.joblib')
    enc = joblib.load('/tmp/enc.joblib')
    model = joblib.load('/tmp/model.joblib')
    # convert json to pandas
    data = pd.DataFrame([pd.Series(data)])
    data = data.replace(['None', 'none', 'null', 'Null', None], np.nan)
    # preprocessing
    data[cat_feat] = imp.transform(data[cat_feat])
    data[cat_feat] = enc.transform(data[cat_feat])
    # predict
    return str(model.predict(data[num_feat+cat_feat])[0])


def proba(request):
    """Responds to any HTTP request.
    Args:
        request (flask.Request): HTTP request object.
    Returns:
        The response text or any set of values that can be turned into a
        Response object using
        `make_response <http://flask.pocoo.org/docs/1.0/api/#flask.Flask.make_response>`.
    """
    logging.info('Starting a new request...')
    download_model()

    request_json = request.get_json()
    if request.args and 'message' in request.args:
        return predict(request.args.get('message'))
    elif request_json and 'message' in request_json:
        return predict(request_json['message'])
    else:
        return f'Failed to read data to predict'

request.json

{
	"message": {
        "Id": 1461,
        "MSSubClass": 20,
        "MSZoning": "RH",
        "LotFrontage": 80.0,
        "LotArea": 11622,
        "Street": "Pave",
        "Alley": null,
        "LotShape": "Reg",
        "LandContour": "Lvl",
        "Utilities": "AllPub",
        "LotConfig": "Inside",
        "LandSlope": "Gtl",
        "Neighborhood": "NAmes",
        "Condition1": "Feedr",
        "Condition2": "Norm",
        "BldgType": "1Fam",
        "HouseStyle": "1Story",
        "OverallQual": 5,
        "OverallCond": 6,
        "YearBuilt": 1961,
        "YearRemodAdd": 1961,
        "RoofStyle": "Gable",
        "RoofMatl": "CompShg",
        "Exterior1st": "VinylSd",
        "Exterior2nd": "VinylSd",
        "MasVnrType": "None",
        "MasVnrArea": 0.0,
        "ExterQual": "TA",
        "ExterCond": "TA",
        "Foundation": "CBlock",
        "BsmtQual": "TA",
        "BsmtCond": "TA",
        "BsmtExposure": "No",
        "BsmtFinType1": "Rec",
        "BsmtFinSF1": 468.0,
        "BsmtFinType2": "LwQ",
        "BsmtFinSF2": 144.0,
        "BsmtUnfSF": 270.0,
        "TotalBsmtSF": 882.0,
        "Heating": "GasA",
        "HeatingQC": "TA",
        "CentralAir": "Y",
        "Electrical": "SBrkr",
        "1stFlrSF": 896,
        "2ndFlrSF": 0,
        "LowQualFinSF": 0,
        "GrLivArea": 896,
        "BsmtFullBath": 0.0,
        "BsmtHalfBath": 0.0,
        "FullBath": 1,
        "HalfBath": 0,
        "BedroomAbvGr": 2,
        "KitchenAbvGr": 1,
        "KitchenQual": "TA",
        "TotRmsAbvGrd": 5,
        "Functional": "Typ",
        "Fireplaces": 0,
        "FireplaceQu": null,
        "GarageType": "Attchd",
        "GarageYrBlt": 1961.0,
        "GarageFinish": "Unf",
        "GarageCars": 1.0,
        "GarageArea": 730.0,
        "GarageQual": "TA",
        "GarageCond": "TA",
        "PavedDrive": "Y",
        "WoodDeckSF": 140,
        "OpenPorchSF": 0,
        "EnclosedPorch": 0,
        "3SsnPorch": 0,
        "ScreenPorch": 120,
        "PoolArea": 0,
        "PoolQC": null,
        "Fence": "MnPrv",
        "MiscFeature": null,
        "MiscVal": 0,
        "MoSold": 6,
        "YrSold": 2010,
        "SaleType": "WD",
        "SaleCondition": "Normal"
    }
}